Master Data Coordinator III

Key Responsibilities

Data Engineering & Integration

• Assist in developing, testing, and maintaining data pipelines and ETL processes.
• Support data integration activities from multiple enterprise systems and data sources.
• Help monitor and troubleshoot data processing jobs to ensure reliability and performance.
• Participate in data migration, validation, and reconciliation activities.

Master Data Management (MDM)

• Support the maintenance and enhancement of enterprise master data models.
• Assist in data quality analysis, data cleansing, and governance activities.
• Help document business rules, data definitions, and master data standards.
• Participate in data stewardship initiatives to improve data consistency and accuracy across systems.

Data Modeling & Analytics

• Assist in creating conceptual, logical, and physical data models under the guidance of senior team members.
• Support data warehousing and business intelligence initiatives.
• Collaborate with stakeholders to understand reporting and analytics requirements.
• Help create documentation, process diagrams, and data flow mappings.

Cloud & Modern Data Platforms

• Support development activities within Databricks and cloud-based data environments.
• Learn and apply technologies such as Apache Spark, Delta Lake, SQL, and Python.
• Participate in CI/CD, DevOps, and automation initiatives related to data engineering solutions.

Collaboration & Continuous Improvement

• Work closely with MDM, Data Quality, Integration, and Analytics teams.
• Participate in Agile ceremonies, sprint planning, and team discussions.
• Contribute ideas to improve data processes, automation, and operational efficiency.
• Stay current with emerging data engineering and analytics technologies.

Qualifications

Required Education

• Bachelor's Degree in:
• Computer Science
• Data Science
• Information Technology
• Computer Engineering
• Industrial Engineering
• Mathematics
• Statistics
• Or a related technical discipline

Experience

• Fresh graduates are encouraged to apply.
• Internship, academic projects, or capstone experience involving databases, ETL, analytics, or cloud technologies is an advantage.

Preferred Technical Skills

Database & Query Languages

• Basic knowledge of SQL
• Understanding of relational databases and data structures
• Programming
• Exposure to Python, Java, Scala, or similar programming languages
• Data & Analytics
• Basic understanding of:
• Data Warehousing
• Data Quality concepts
• Data Governance
• Master Data Management (MDM)
• Business Intelligence reporting
• Mathematics
• Statistics
• Or a related technical discipline
• Cloud & Modern Data Platforms (Exposure to one or more of the following preferred):
• Databricks
• Azure
• AWS
• Google Cloud Platform (GCP)
• Apache Spark

Additional Preferred Skills

• Familiarity with Git or version control systems
• Knowledge of Agile methodologies
• Experience with Tableau, Power BI, or similar reporting tools
• Understanding of ETL concepts and data integration processes

Core Competencies

• Strong analytical and problem-solving skills
• High attention to detail and focus on data accuracy
• Curiosity and willingness to learn new technologies
• Good verbal and written communication skills
• Strong collaboration and teamwork skills
• Ability to manage multiple priorities and tasks
• Creative mindset for identifying process improvement opportunities
• Commitment to data quality and continuous improvement